6 October 2010 Grinding precision forecasting in optical aspheric grinding using artificial neural network and genetic algorithm
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Proceedings Volume 7655, 5th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Advanced Optical Manufacturing Technologies; 76551L (2010) https://doi.org/10.1117/12.864454
Event: 5th International Symposium on Advanced Optical Manufacturing and Testing Technologies, 2010, Dalian, China
Abstract
A new approach based on an artificial neural network (ANN) was presented for the prediction of machining precision of optical aspheric grinding. The ANN model is based on Globally Convergent Adaptive Quick Back Propagation algorithm (GCAOBP). A genetic algorithm (GA) was then applied to the trained ANN model to predict the gridding precision. The integrated GCAOBP-GA algorithm was successful in predicting the Root Mean Square of profile error (RMS) of optical aspheric workpiece in parallel grinding method using machining parameters. The results of experiments have shown that RMS of machined workpiece in parallel grinding can be predicted effectively through this approach.
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Chen Jiang, Chen Jiang, Yinbiao Guo, Yinbiao Guo, Qingqing Yang, Qingqing Yang, Chunguang Han, Chunguang Han, } "Grinding precision forecasting in optical aspheric grinding using artificial neural network and genetic algorithm", Proc. SPIE 7655, 5th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Advanced Optical Manufacturing Technologies, 76551L (6 October 2010); doi: 10.1117/12.864454; https://doi.org/10.1117/12.864454
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